In a wireless communication system it is often desirable to locate users who are making calls. Applications for such a technology would include locating subscribers requesting 911-emergency services, so that police/fire/ambulance services could be dispatched to a user making a call. Other applications include cellular fraud detection, police investigations, and the like.
Previous cellular systems lacked sufficient resolution or accuracy to implement these applications. For example, in AMPS (Advanced Mobile Phone System) Cellular Radio, a user could be located within a cell by determining which base station antenna was used to serve the user. However a cell could be as large as 3-5 miles in radius, making this information practically useless for locating the subscriber. In addition, if the best serving base station is not the closest base, the possible range of locations for the subscriber may be even larger, and thus much less precise. Therefore, this method is not sufficient for most purposes.
Since many of the dense urban cell sites are now much smaller in radius, and many of the urban/suburban cell sites are now sectorized, the use of sectored antennas limits a channel's service area to just one sector, or portion of a cell, which significantly reduces the distinguishable coverage areas within a cell. However, the area even in these smaller sectors or cells can still be more than one square mile, and the closest cell still may not be best serving cell, thus introducing uncertainty, and making this method of location finding of little practical use. Other radio systems like US Digital Cellular (USDC) and (Group Speciale Mobile (GSM) use this same method of identifying the cell or sector, and thus may do no better than the AMPS system.
While there are other location finding alternatives, such as the use of Global Positioning System (GPS) units at the subscriber unit, these typically increase size, weight, and battery drain, and are thereby too costly to be used by most subscribers.
Another known method of finding location is to locate a subscriber unit at known locations throughout the coverage area of the cellular system while the base stations record signal characteristics associated with the received signals. These characteristics are then stored in a database along with the location previously recorded at the time the measurements were made. The "known location" may be determined with a GPS receiver. Later, when radio signals with similar characteristics are measured again by the base station, the location in the database with the closest match is assumed to be the location of the user.
This method suffers from a number of problems. First, locations in the database are limited to the locations that were measured, wherein such measurements may have been taken by driving or walking through the coverage area. It is difficult to drive an area and take enough measurements to have an accurate database for finding a location with a useful resolution. To get location finding resolutions down below 100 feet, a fine grid of locations must be measured, including both sides of the street, parking lots, pedestrian walkways, parks, and more.
And second, even if it was possible to measure all the important areas, small changes to a cell site configuration or location would require remeasuring all the locations in the area. Adding a new building in the service area, or erecting some other structure that affects signal propagation, would also require remeasuring all locations to recalibrate the system.
Thirdly, the GPS measurements must be highly accurate. If tall buildings are present in the GPS measurement area, even the best GPS measurement augmented by differential correction is not accurate enough to locate the user with the required resolution. Measurements taken in dense urban environments (i.e., in locations surrounded by tall buildings or other structures that block GPS signal reception) often have significant errors, erroneously locating the user on an adjacent street, or inside buildings, etc.. Thus, methods that rely exclusively on actual base station measurements are quite difficult to implement in practice, and are prone to errors that limit the accuracy of these methods.
Other location-finding methods have been proposed and demonstrated in an AMPS phone system, wherein the time difference of arrival of a signal transmitted from a subscriber and received at two or more base stations is measured. Locations corresponding to constant time differences between arriving signals may be plotted in a model of the coverage area as a set of hyperbolas--a set of points 116-122 (see FIG. 1) that define possible locations of the subscriber. If three sites can measure the signal from the subscriber and determine a time difference of arrival between each, then three time differences, representing three hyperbolas can be estimated. At least two time differences are needed to estimate a location. Reference numerals 120 and 122 illustrate lines of constant time difference intersecting at a point 102, representing the location of the subscriber. U.S. Pat. No. 5,317,323 to Kennedy, et al. describes the combined use of time difference of arrival and angle of arrival to obtain an improved location estimate when the measurement process is imprecise or unstable.
Referring now to FIG. 1, there is depicted a wireless communication system service area 100. As illustrated, subscriber unit 102 is located in the midst of base station antennas 104, 106, and 108. Angles of arrival for signals received at base station antennas 104, 106, and 108 are shown at reference numerals 110, 112, and 114, respectively. Locations in wireless communication service area 100 having a constant time difference of arrival may be shown as hyperbolas, such as hyperbolas 116, 118, 120, and 122. For example, hyperbolas 116, 118, and 120 represent three distinctly different time differences measured between sites 104 and 106. At any point on these lines, the time difference between the propagation delay (or time of flight (TOF)) to antenna 104 and the propagation delay to antenna 106 is a constant. Thus, considering time difference of arrival alone, a subscriber unit may be at any point on the line corresponding to a certain time difference measurement.
Similarly, hyperbola 122 represents another time difference contour measured between sites 106 and 108. Thus, by having two separate time difference estimates between two pairs of sites, a distinct location may be found, as shown by the intersection of lines 120 and 122. Likewise, angle of arrival information may be used alone or in combination with the time measurements to find a subscriber's location.
Angle of arrival measurements may be made with sectorized antenna methods, such as shown in FIG. 2, or with a fixed beam array antenna, as shown in FIG. 3. Such fixed beam array antennas can form very narrow beams, which allows the angle of arrival to be determined with a much higher resolution. Further, with other methods known in the art, such as adaptive beam forming and direction finding, even greater resolution may be obtained in determining the angle of arrival of a received signal.
Referring now to FIG. 3, a set of antenna elements 130 is shown. Each antenna is connected to an input (4 inputs in this example) of a Butler Matrix. A Butler Matrix is commonly known in the art. Its function is to combine the inputs from the four antenna elements with the proper amplitudes and phases, to produce the effect of four distinct sector antennas pointing in four distinct directions. This technique may be referred to as "beam forming." Outputs 132 represent the signals that would be received by the four "beam formed" sector antennas. Thus, when used in a location finding system, the four different beams may provide a way to estimate the direction of an arriving signal by detecting the beam which had the first arrival of the received signal. In like fashion, FIG. 2 illustrates the use of fixed beam sectorized antennas arranged in different pointing directions. Antennas 134, 136, and 138 each point in a different direction, and by monitoring the signal level at their respective outputs, 140, 142, and 144, an estimate of the direction of arrival may be obtained as mentioned above.
All of the location-finding methods that rely on time difference of arrival and or angle of arrival attempt to estimate the location of the subscriber by assuming a clear path from the subscriber to the base. With such a clear path, it is assumed that the signals propagate in a straight line, the time delay of the propagation is directly a function of the distance traveled, and the angle of arrival 110, 112, and 114 represents the direction, in a straight line, from the base to the subscriber.
When operating in a cluttered urban area, these assumptions create significant problems. In the cluttered urban area, the signals Typically do not propagate in a straight line; rather they are reflected off buildings, and diffracted around corners to reach the base station antenna via an indirect path. For example, see paths 172-180 in FIG. 2. If "clear path" assumptions are used, the location estimate will probably be invalid since both the time differences and angles are affected by the environment. Thus, the problem of location finding in a cluttered area is complicated because there is no straight forward relationship between the receive signal and the location of the subscriber.
Therefore, there remains a need for an improved, cost-efficient approach for locating subscribers in a cluttered area of a communications system, wherein indirect or non-line-of-sight propagation signal paths are taken into account, and signal characteristics need not be empirically measured.